Senior AI/ML Engineer - Job Description
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Job description
- Design, develop, and deploy end-to-end machine learning and AI solutions for enterprise applications.
- Build and optimize predictive models using supervised, unsupervised, and deep learning techniques.
- Develop Generative AI applications using LLMs, RAG, embeddings, vector databases, and prompt engineering.
- Work with frameworks such as PyTorch, TensorFlow, Scikit-learn, Hugging Face, LangChain, and LlamaIndex.
- Develop NLP, text classification, recommendation, forecasting, and anomaly detection solutions as required.
- Build production-ready AI/ML services and integrate models with enterprise applications through REST APIs and microservices.
- Develop data preprocessing, feature engineering, model training, validation, and evaluation pipelines.
- Implement MLOps practices for model deployment, monitoring, versioning, and continuous improvement.
- Work with cloud-based AI/ML services across AWS, Azure, or Google Cloud Platform.
- Collaborate with data engineers, software engineers, architects, product teams, and business stakeholders.
- Optimize models for scalability, performance, accuracy, latency, and cost.
- Establish responsible AI practices including model monitoring, security, governance, and explainability.
- Mentor junior engineers and contribute to technical architecture and engineering best practices.
Requirements
We are looking for a highly experienced Senior AI/ML Engineer with 10+ years of software engineering and machine learning experience to design, develop, and deploy intelligent, scalable AI/ML solutions. The ideal candidate will have strong expertise in Python, machine learning, deep learning, Generative AI, NLP, cloud platforms, and data engineering, along with hands-on experience taking ML solutions from experimentation through production., * 10+ years of experience in software engineering, data science, machine learning, or AI engineering.
- Strong programming experience with Python.
- Hands-on expertise in Machine Learning and Deep Learning.
- Strong knowledge of NLP, Generative AI, LLMs, and transformer-based models.
- Experience with RAG, embeddings, vector databases, prompt engineering, and LLM evaluation.
- Experience with frameworks such as PyTorch, TensorFlow, Scikit-learn, Hugging Face, LangChain, or LlamaIndex.
- Strong understanding of SQL and experience working with large datasets.
- Experience developing and deploying REST APIs / microservices for AI/ML applications.
- Hands-on experience with at least one major cloud platform: AWS, Azure, or Google Cloud Platform.
- Experience with Docker, Kubernetes, Git, CI/CD, and cloud deployment.
- Understanding of MLOps, model lifecycle management, monitoring, and model versioning.
- Strong knowledge of data structures, algorithms, software design principles, and scalable system architecture.
Preferred Skills
- Experience with Azure OpenAI, AWS Bedrock, Amazon SageMaker, Azure Machine Learning, or Vertex AI.
- Experience with FAISS, Pinecone, Azure AI Search, OpenSearch, Milvus, or similar vector databases.
- Knowledge of Kafka, Spark, Databricks, Snowflake, or modern data platforms.
- Experience building AI agents, Agentic AI, tool calling, and multi-agent systems.
- Familiarity with LangGraph, Semantic Kernel, MCP, or similar agent frameworks.
- Experience with model fine-tuning, LoRA/QLoRA, and open-source LLMs.
- Knowledge of AI security, responsible AI, data privacy, and governance.
- Experience working in Agile/Scrum environments., Bachelor’’s or Master’’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related field., The ideal candidate is a hands-on senior engineer who can bridge AI/ML research, software engineering, data engineering, and production deployment. They should be capable of independently designing enterprise AI solutions while also contributing to architecture, technical leadership, and mentoring.
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